The time-dependent behaviour of soft and clayey soils treated with Deep Cement Mixing (DCM) columns is important for analyzing the long-term performance of civil engineering infrastructures. Previous studies on DCMinstalled composite soil (CS) have primarily focused on examining the soil strength and stiffness characteristics. The limited focus on the time-dependent settlement and stress-strain distribution of CS underscores the need for a more comprehensive understanding of this complex phenomenon. In this study, a lab-scale physical ground model is designed and developed to investigate the time-dependent settlement profile of the composite Montmorillonitic Clay soil (MMC). The settlement behaviour of the ground model is assessed using Creep Hypothesis B and the results are further validated with the Power Law Model. Additionally, a FEM-based numerical simulation is performed to examine the time-dependent settlement and the stress distribution between the column and surrounding clay soil at different depths. The results from the physical model test show that the time-dependent parameter of the ground model (i.e., DCM column installed in MMC) is proportionate to the loading rate until the failure of the DCM column is reached. However, the time-dependent parameter was found to be decreased by 59.04 % in the post-failure phase of the DCM column. This reduction indicates that the DCM column was the primary load-bearing component before its failure. The numerical study shows that the pore water pressure dissipation in the clay soil and DCM column interface was similar at various depths. The top and bottom sections of the DCM column possess higher stress levels, which demonstrates its susceptibility for failure in the DCM column.

Soft clays exhibit significant challenges in geotechnical engineering due to their low permeability, high compressibility, and susceptibility to settlement under applied loads. These geological factors pose unique difficulties in predicting long-term settlement accurately and efficiently, particularly through Class C prediction methods that involve iterative processes with complex numerical models. To address these challenges, this study presents an efficient approach for Class C prediction of long-term settlement in soft clays. This approach integrates Bayesian updating with structural reliability methods (BUS) and the general simplified Hypothesis B method which is a semi-analytical method based on one-dimensional elastic visco-plastic (1D EVP) model. Unlike previous research that used Response Surface Model (RSM) with polynomial function for consolidation evaluation, the proposed approach enhances both accuracy and performance consistency under varying conditions. Additionally, by leveraging analytical solutions instead of iterative small-time steps required by Finite Element Method (FEM) or Finite Difference Method (FDM), the computational efficiency is also enhanced. The effectiveness of the proposed approach is demonstrated through its application to an embankment improved with prefabricated vertical drain (PVD) in Ballina, New South Wales, Australia. Comparative analyses demonstrate that the predicted settlements from this study, using only the monitoring settlement data collected prior to the 76th day of the project, align closely with the results from established RSM and FEM-based Bayesian back analysis approaches. The obtained results also indicate that the predicted settlements, based on 76 days of monitoring data, closely match field measurements at various depths, whether relying solely on settlement data or integrating additional pore water pressure data. For the Ballina embankment, over 40,000 consolidation analyses required for a single BUS simulation can be completed within 10 h using the general simplified Hypothesis B method, compared to months it might take with FEM or FDM approaches. This makes the proposed approach a practical tool for geotechnical engineers, enabling reliable settlement predictions early in the project timeline while maintaining low computational costs.